Superlinked provider of a solution for turning complex data into vector embeddings secures $9.5million in seed funding. Index Ventures led the round, in which Theory Ventures, 20Sales, Firestreak, and a number of tech professionals also participated. With the money, the business plans to grow its product line and fulfill market demand by scaling up.
Superlinked, a computational and data engineering platform founded by Daniel Svonava and Ben Gutkovich, optimizes retrieval control, quality, and efficiency in real time by turning data into vector embeddings. This allows businesses to create analytics, RAG, search, and recommendation systems.
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To increase its reach and capabilities, Superlinked has already partnered on integrations with a number of software companies, including as Redis, Dataiku, Starburst, MongoDB, and others.
The startup, which also maintains offices in Budapest, Hungary, and London, UK, opened enterprise client contracts and released a private alpha of their software to enable data retrieval and feature engineering for machine learning systems.
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About Superlinked
Superlinked is a computing framework designed to transform complex data into vector embeddings for use in feature engineering and information retrieval systems. The method used by data engineers to convert data into vector embeddings. Converting millions of documents and 1 billion user clicks into vectors is more impressive than building LLM demos.
